Introduction
The leading causes of morbidity and mortality, such as cardiovascular disease and cancer, can be prevented through changes in key behaviors such as increasing physical activity, improving dietary intake, limiting alcohol consumption and stopping/not starting smoking (Global Burden of Disease Collaboration,
2015). Although the majority of interventions are designed to change the behaviors of adults, rather than children (e.g., Brunet et al.,
2018), modifying the health behaviors of children is likely to yield the greatest health benefits. The few interventions designed to change children’s behavior are typically targeted at adults (e.g., parents, teachers) or children (e.g., Nixon et al.,
2012), but rarely both adults and children simultaneously. This is a potentially important omission because there are complex interactions between children and adults when it comes to managing health behavior change (e.g., Vallgarda et al.,
2015), and models that suggest that targeting interpersonal processes may exert greater impact than targeting the individual alone (e.g., McLeroy et al.,
1988). The aim of the present research was to test a theory-based behavior change intervention designed to promote both child and adult behavior change simultaneously.
It is clear that for many of the domains in which behavior change is important, the majority of people are already motivated to change (e.g., 68% of US smokers want to quit completely, Centers for Disease Control,
2017). This means that, in addition to considering ways to motivate people, researchers are paying increasing attention to behavior change interventions that will ensure people’s existing good intentions are effectively translated into relevant behavior change. Accumulated research shows that implementation intentions, derived from Heckhausen and Gollwitzer’s (
1987) Rubicon model, are helpful in ensuring that good intentions are translated into action. Implementation intentions differ from other concepts found in models of behavior change (e.g., capabilities, opportunities, and motivations, see Michie et al.,
2014) in so far as implementation intentions can be used to deliver multiple techniques (e.g., valued self-identities, Armitage et al.,
2011; self-incentives, Brown et al.,
2018) that bring about changes in behavior via changes in constructs such as capabilities, opportunities and motivations (Michie et al.,
2014).
Implementation intentions (Gollwitzer,
1993) are ‘if–then’ plans that involve linking critical cues (e.g., times of day, physical locations, internal sensations) with appropriate responses (e.g., self-talk, stimulus control). Specifying critical cues makes the ‘if’ part of the plan salient when it is encountered and the linked responses (‘then’) automatically spring to mind (Gollwitzer & Sheeran,
2006). There is now a large body of work attesting to the effectiveness of implementation intention-based interventions, which typically exert medium-large (
d = 0.65) effects on behavior change (e.g., Gollwitzer & Sheeran,
2006). Despite the potential for implementation intention-based interventions to change diverse behaviors, only a small number of previous studies deployed such interventions among children. Nevertheless, the signs are encouraging and implementation intention formation among children has been shown to help with: Impulse control (Gawrilow et al.,
2011) preventing distractions in the classroom (Wieber et al.,
2011), increasing fruit and vegetable intake (Gratton et al.,
2007), preventing uptake of smoking (Conner & Higgins,
2010), and increasing physical activity (Armitage & Sprigg,
2010). Moreover, the effects are potentially long-lasting. For example, a study aimed at preventing smoking uptake in adolescents showed that the effects of an implementation intention-based intervention were sustained 2 years post-intervention (Conner & Higgins,
2010). However, in each of these cases, implementation intentions were consistently targeted at children thereby ignoring the influence that adults exert on children’s behavior. We thus developed an implementation intention-based intervention with the potential, where necessary, to promote both child and adult behavior change.
The context for the present study was oral health care among children, which is important because dental caries is the most prevalent of all diseases worldwide (Global Burden of Disease Collaboration,
2015). Guidelines to prevent dental caries highlight the importance of health behaviors that depend on a patient’s input, particularly tooth-brushing as well as supervision for children (Department of Health and the British Association for the Study of Community Dentistry,
2009). Thus, maintenance of oral health care among children is an activity that should explicitly be the shared responsibility of children and adults. Development of the intervention is described elsewhere (Davies et al.,
2017), but briefly, it involves a health care professional training both children and adults in the principles of implementation intentions and their formation with the help of a brief animation that was designed for the purposes of the present research. Following exposure to the animation, children and adults together form implementation intentions that they think will change their behavior (e.g., regular teethbrushing, avoiding sugary snacks).
Before proceeding to a full trial, we wanted to test proof of concept and so the aims of the present research were to: (a) test recruitment and retention rates, (b) assess the acceptability of the intervention and research procedures, and (c) generate effect sizes for a future definitive trial.
Discussion
This is the first test of a theory-based behavior change intervention designed explicitly to change both child and adult behavior simultaneously. The study demonstrated that children and adults can be recruited and complete a randomized trial, find the intervention and methods of assessment acceptable, and view the intervention as useful. Thus, the present study demonstrated the feasibility of both the intervention and data collection procedures. Although not designed to test effectiveness, the clinical assessments were consistent with reductions in plaque in the intervention groups, with an increased effect with use of a booster. Together with the size of the effects observed, the present study suggests that it would be useful to proceed to a definitive randomized controlled trial. If proved effective the brief intervention could be integrated into routine practice within the cleft population and has substantial potential for adaptation to address other child and adult health behaviors.
The present research contributes to a small evidence-base showing that implementation intentions can be effective as the basis for interventions designed to change children’s behavior (e.g., Armitage & Sprigg,
2010). This is important because major public health gains will only be achieved with greater emphasis on prevention/intervention in childhood. Moreover, the present means by which people formed implementation intentions (i.e., by watching a video animation) was novel and contributes to an evidence base showing that as long as the “if–then” format is followed, the means by which implementation intentions are delivered can be flexible. Thus, the present research contributes to a literature showing that effective implementation intentions can be self-generated or researcher-provided (Armitage,
2009), administered online (Armitage,
2015) or even placed on the side of wine bottles (Armitage & Arden,
2016), by encouraging children and adults to form implementation intentions by means of an animation. This means that the intervention has the potential to be deployed at scale with high public health reach.
Limitations
Although the present research takes the literature on implementation intentions forward in some important respects, there are potential limitations. First, while the use of home visits for data collection and intervention delivery was acceptable and feasible it may not be a practical model for a larger study. However, a minority of assessments and interventions (n = 10, 17%) were completed in clinics. Given that there seemed to be no difference in acceptability between home visits versus clinic administration, it might be the case that delivering the intervention in clinics alongside routine check-ups is more cost-effective than home visits. Provision within the clinics would also provide opportunities for families unable to converse in English to receive the intervention with interpreters on hand to facilitate routine consultations.
A second limitation is that although dental care practitioners were blinded to the initial clinical assessments, the distances of homes from cleft centers meant that it was not possible to send a blinded assessor to the 6-month follow-up visits. This lack of blinding at follow-up raises the possibility of bias in the clinical assessments. However, follow-up assessments of gingivitis in the intervention condition produced a notable increase in gingivitis (+ 7.69%) at the same time as a marked decrease in plaque (− 28.46%), which might suggest some level of confidence in the objectivity of the assessments. Nevertheless, it would be preferable to ensure that all clinical assessments are blinded, which might be achievable in a clinic-based setting.
Third, implementation intentions operate by increasing the salience of critical cues and automatizing cue-response links (Gollwitzer & Sheeran,
2006). As yet, there is no agreed way of directly measuring this deployment of strategic automaticity outside the laboratory, meaning there was no way of assessing process, which is a further potential limitation.
Acknowledgements
The NHS Health Research Authority, Research Ethics Committee reference 15/WM/0352, approved the study. The trial was registered with the ISRCTN No.: 45791053. This paper presents independent research funded by the National Institute for Health Research (NIHR) under its Research for Patient Benefit (RfPB) Programme (Grant Reference Number PB-PG-0613-31022). The NIHR Manchester Biomedical Research Centre and NIHR Greater Manchester Patient Safety Translational Research Centre also supported the research. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. We would like to thank dental care practitioners Jessica Butcher, Caroline Connolly and Laura Stannage who recruited participants and collected the data as well as Saff Bahm, Haydn Bellardie, Vicky Brand, Nancy Bray, Victoria Clark, Karen Davies, Susana Dominquez-Gonzalez, Lars Enocson, Kat Kandiah, Yin-Ling Lin, Deborah Moore, James Munro, Kevin O’Brien, Bill Shaw, Martin Tickle, and Cath Wright who advised on the development of the intervention and the study.
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